Left Shift Data Platform: How to overcome early-stage startup challenges to become data-driven

The structure of the article is as follows.

• What is a data platform?
• Why do you need a data platform?
• Challenges startups face in becoming data-driven
• What strategies can you adopt to become data-driven?

What is a data platform?

Data platforms integrate and process business and product data to provide valuable insights. These insights include dashboards, KPI metrics, growth metrics, and machine learning models for prediction and better decision-making. Data platforms allow startups to adapt and grow in competitive markets and make better business decisions. Data platforms serve as the backbone for startups looking to become data-driven, providing better customer insights and competitive advantage. In today’s AI era, every new digital product must be integrated with AI models and analytics to grow your audience and compete in the market with innovative products.

Why should startups be data-driven in the first place?

Data is the new oil of the digital economy. It is considered to be the lifeblood of any business. Peter Drucker once said:You can’t manage what you can’t measure.In today’s world, it is impossible to measure business growth without using data efficiently.

Over the past few years, I have had the opportunity to work with several startups and meet with many senior executives, including chiefs, heads, and product directors. In conversations with leaders of mid-stage startups, I was surprised to learn that there are still early-stage companies that don’t want to consider investing time and resources in building a data platform. Instead, they want to just focus on building the product itself.

I wasn’t too shocked after reading the survey conducted by IW Germany More than 1,000 companies participated in the survey.

Only 30% of small businesses manage and utilize their data effectively. This means that there are still 70% of companies that are not promoting data-driven decision-making, which is a significant number.

To increase your chances of success during your startup journey, you should prioritize building a data platform first.One of the studies by McKinsey The Global Institute makes that clear.

A data-driven organization is twenty three Your chances of acquiring customers are many times higher, 6 Double your chances of retaining your customers. 19 The potential for profit increases many times over.

new vantage has conducted research for eight consecutive years and reported in a recent study.

For 2023, 91.9% of companies will deliver value from their data, with predictions for next year increasing to 98.2%. However, they also concluded that 79.8% of businesses still struggle to overcome the challenges of becoming data-driven.

With 10 years of experience in data, we are now in our 20th year of talking about the importance of data leadership and data-driven decision-making, but we still have a lot of questions about data leadership and the importance of data-driven decision-making. I can’t imagine there is another world out there that I haven’t considered or prioritized. First of all, be data-driven.

Problems with early-stage startups

I like to dig deep and understand startup pain points and current limitations. My findings are:

1. Fee: they didn’t have money Invest in data, resources, and infrastructure early.
2. way of thinking: They combined this term with data platforms big data Infrastructure is complex and requires a lot of resources, money, and highly specialized engineers along with the infrastructure.
3. no time: They want to focus on building their product or service to stand out because there aren’t enough of them. time.
4. Where do I start? Some companies know they need a data platform, but their limited knowledge prevents them from building an architecture. Decisions made for complex reasons data stack.

cost-effective strategy

If you or your business are experiencing any of the challenges listed above. In that case, I would like to shift my focus to a cost- and time-efficient data strategy that I advised one of his startup clients. Our clients have successfully built the pillars of their data platform.

• overcome costs, Budget constraints:
  1. Start with a small, minimally viable data solution that addresses your most important data needs and scale as your business grows.
  2. Leverage open source tools: Many open source data tools and platforms such as Airflow, Airbyte, Mage.ai, Data Build Tools (DBT), and Python can significantly reduce costs.
  3. consider Intermediate or mid-level engineer Some experience is sufficient to set up your first initial data platform.
  4. How to attract engineers Stock-based compensation. Many talented individuals are willing to contribute to promising startup ideas in exchange for equity.
• Simplify your big data infrastructure:

1. 1. Don’t try to become data-driven with big data technologies early in your career unless you really have to. A simple scripting programming language like Python or a cloud-based data platform like Google Cloud Platform, AWS, or Azure can be a kickstart. These services offer a pay-as-you-go model that scales with your business, eliminating the need for large up-front investments.
   2. Choose a managed or serverless service. Simplify the complexity of data infrastructure setup and maintenance, and provide support and maintenance.

1. 1. Integrate data into product development: Data should be considered as part of the product offering and not as a separate entity. This integration helps create more user-centric products and services.
   2. Adopt an agile methodology: Implement agile methodologies that enable rapid iteration and incorporate data analysis into the development process.

• Limited data knowledge and complex data stacks:

Talk to a data expert: A short-term consultation with a data expert can help you set up your data infrastructure and build a data platform team that aligns with your business goals.

conclusion

Data platforms are the foundational pillars of any business, allowing them to make decisions based on data, trends, and customer experience without relying solely on second-hand views. Initially, you don’t need a complex big data architecture solution. Building the right data and product strategy requires efficient use of time and resources. Building a product is essential, but ignoring a data platform in the early stages can leave you behind in a competitive market and improving customer engagement. The above research clearly shows a potentially increased chance of success. That’s why we need to shift left and prioritize data platforms alongside product development.

Madiha Khalidis a Lead Data Engineer with over 10 years of experience in the technology industry.